Objective To analyze the trends in the disease burden of pertussis in China from 1990 to 2021, and to provide a basis for the development of effective prevention and control strategies. Methods Using the 2021 Global Burden of Disease Study (GBD) database, the incidence, mortality, and disability-adjusted life years (DALYs), as well as the age-standardized rates of pertussis in China from 1990 to 2021 were analyzed. Descriptive statistical methods were employed to analyze the characteristics of the pertussis disease burden, and the Joinpoint regression model was used to analyze the trends in pertussis disease burden. Results From 1990 to 2021, the incidence, mortality, and DALYs of pertussis in China decreased from 1 503 800 cases, 10 951 deaths, and 954 900 person-years to 65 400 cases, 548 deaths, and 46 500 person-years, representing a decrease of 95.65%, 95.00%, and 95.13%, respectively. The corresponding age-standardized rates also decreased by 93.58%, 92.47%, and 92.53%, respectively. The Joinpoint regression model revealed a significant downward trend in the age-standardized incidence, mortality, and DALYs rates for pertussis (AAPCs were -8.32%, -9.65%, and -9.58%, respectively, P<0.001). The disease burden was slightly higher in females than in males, with the majority of cases occurring in children under 10 years old, particularly in infants under 1 year old, where the burden was the heaviest. As age increased, the disease burden decreased. Conclusion Between 1990 and 2021, the overall disease burden of pertussis in China showed a significant downward trend, with gender and age differences. Special attention should be given on the prevention and control of pertussis in children under 10 years old, especially in infants under 1 year old.

BACKGROUND:Establishing a nomogram prediction model for postoperative pulmonary infection in hip fractures and taking early intervention measures is crucial for improving patients'quality of life and reducing medical costs. OBJECTIVE:To construct a nomogram risk prediction model of postoperative pulmonary infection in elderly patients with hip fracture,and provide theoretical basis for feasible prevention and early intervention. METHODS:Case data of 305 elderly patients with hip fractures who underwent surgical treatment at Wuxi Traditional Chinese Medicine Hospital Affiliated to Nanjing University of Chinese Medicine between January and October 2020(training set)were retrospectively analyzed.Using univariate and multivariate logistic regression analysis and Hosmer-Lemeshow goodness of fit test,receiver operating characteristic curve was utilized to analyze the diagnostic predictive efficacy of independent risk factors and joint models for postoperative pulmonary infections.Tools glmnet,pROC,and rms in R Studio software were applied to construct a nomogram model for predicting the risk of postoperative pulmonary infection in elderly patients with hip fractures,and calibration curves were further drawn to verify the predictive ability of the nomogram model.Receiver operating characteristic curves,calibration curves,and decision curves were analyzed for 133 elderly patients with hip fractures(validation set)receiving surgery at the same hospital from November 2022 to March 2023 to further predict the predictive ability of the nomogram model. RESULTS AND CONCLUSION:(1)The postoperative pulmonary infection rate in elderly patients with hip fractures in this group was 9.18%(28/305).(2)Single factor and multivariate analysis,as well as forest plots,showed that preoperative hospitalization days,leukocyte count,hypersensitive C-reactive protein,and serum sodium levels were independent risk factors(P<0.05).The Hosmer-Lemeshow goodness of fit test showed good fit(χ2=4.57,P=0.803).Receiver operating characteristic curve analysis was conducted on the independent risk factors and their joint models mentioned above,and the differentiation of each independent risk factor and joint model was good,with statistical significance(P<0.05).(3)The graphical calibration method,C-index,and decision curve were used to validate the nomogram prediction model.The predicted calibration curve was located between the standard curve and the acceptable line,and the predicted risk of the nomogram model was consistent with the actual risk.(4)The validation set used receiver operating characteristic curve,graphic calibration method,and decision curve to validate the prediction model.The results showed good consistency with clinical practice,indicating that the model had a good fit.The nomogram risk prediction model constructed for postoperative pulmonary infection in elderly patients with hip fractures has good predictive performance.The use of the nomogram risk prediction model can screen high-risk populations and provide a theoretical basis for early intervention.

Objective To explore the role and mechanism of RNA demethylase fat mass and obesity-associated protein(FTO)in the ferroptosis in testicular interstitial cells induced by di(2-ethylhexyl)phthalate(DEHP).Methods Forty 3-week-old C57BL/6 male mice were randomly divided into a control group(corn oil)and 3 dosed DEHP treatment groups(5,250 and 500 mg/kg),and received an intragastric infusion of corresponding agents for 35 d,respectively.After mouse testicular interstitial TM3 cells was treated with 0,100,200 and 400 μmol/L mono-2-ethylhexyl phthalate(MEHP)for 24 h,corresponding plasmids were transfected to construct Fto overexpressing TM3 cells.Serum testosterone level was detected by ELISA,expression of testicular proteins was detected with immunohistochemical assay,and contents of Fe2+,malondialdehyde(MDA)and lipid peroxides in the testicle were detected by colorimetry.Methylated RNA immunoprecipitation,RT-PCR,and Western blotting were used to detect the level of N6-methyladenosine(m6A)modification.Results In the mice exposed to 250 and 500 mg/kg DEHP,the serum testosterone level was significantly reduced(P＜0.01),contents of Fe2+,MAD and lipid peroxides in testicular tissue were obviously increased(P＜0.01),and protein levels of RNA demethylase FTO,and ferroptosis related molecules ferritin heavy chain 1(FTH1)and glutathione peroxidase 4(GPX4)were significantly down-regulated(P＜0.05),while those of transferrin receptor(TFRC),ferroportin(FPN),cyclooxygenase-2(COX-2),and acyl-CoA synthetase long-chain family member 4(ACSL4)were notably up-regulated(P＜0.05).MEHP treatment for 24 h resulted in remarkably decreased cell viability in the TM3 cells,increased production of intracellular reactive oxygen species(ROS),reduced mitochondrial membrane potential(MMP)(P＜0.01),down-regulated mRNA and protein levels of Fto(P＜0.01),and the changes in other ferroptosis related proteins were consistent with the trend in testicular tissue,indicating ferroptosis in testicular interstitial cells.Intervention with ferroptosis inhibitor Fer-1 or overexpression of Fto significantly inhibited MEHP-induced toxicity and ferroptosis in TM3 cells(P＜0.05),and overexpression of Fto reduced the m6A modification of Gpx4 and Fth1 mRNA(P＜0.05).Conclusion Abnormal m6A modification of Gpx4 and Fth1 caused by inhibiting FTO expression may be the mechanism of ferroptosis in testicular interstitial cells induced by DEHP.

Objective:To identify the relationship between the CT arterial radiomics score and the treatment response to neoadjuvant therapy for pancreatic cancer.Methods:The clinical data of 243 pancreatic cancer patients who received surgical resection after neo-adjuvant therapy in the First Affiliated Hospital of Naval Medical University from March 2017 to March 2023 were retrospectively analyzed. Based on the tumor regression grade (TRG), the patients were divided into good response group (TRG 0-1, n=30) and non-good response group (TRG 2-3, n=213). The clinical, radiological and pathological features were compared between two groups. Fully-automated segmentation tool was used for segmenting the arterial CT scan of pancreatic tumor before and after treatment. Python package was applied to extract the radiomics features of tumors after segmentation and the extracted features were reduced and chosen using the least absolute shrinkage and selection operator (Lasso) logistic regression algorithm. Lasso logistic regression formula was applied to calculate the arterial radiomics score. Univariate and multivariate logistic regression models were used to analyze the association between arterial radiomics score and treatment response to neoadjucant therapy. Receiver operating-characteristics (ROC) curve was drawn and area under curve (AUC), specificity, sensitivity and accuracy for evaluating the treatment response were calculated. The clinical usefulness of arterial radiomics score for diagnosing the response of neoadjuvant treatment for pancreatic cancer were determined by decision curve analysis (DCA) . Results:A total of 330 arterial radiomics CT features were obtained, and 9-selected arterial phase features associated with treatment response were determined after being reduced by the Lasso logistic regression algorithm. Univariate analysis showed that the arterial radiomics score, three-dimensional diameter after neoadjuvant therapy, pancreatic contour, T stage, N stage, Peri-pancreatic nerve invasion, lymph-vascular space invasion (LVSI) and invasion of duodenum were all associated with treatment response (all P value <0.05). Multivariate logistic regression analyses confirmed that arterial radiomics score was obviously associated with the neoadjuvant treatment response ( P<0.001). At the cut-off value of 1.93, AUC of the arterial radiomics score for diagnosing neoadjuvant treatment response was 0.92, and the specificity, sensitivity and accuracy was 86.7%, 84.5% and 84.8%. DCA demonstrated that when the percentage for predicting the treatment response by using the arterial radiomics score was >0.2, the patients could benefit from the application of arterial radiomics score for evaluating neoadjuvant therapy response. Conclusions:The arterial radiomics score was strongly correlated with the neoadjuvant treatment response of pancreatic cancer, and can accurately predict neoadjuant treatment efficacy.

Objective:To analyze the risk factors of postoperative bleeding after CT-guided percutaneous fly biopsy, and to construct a nomogram model for predicting postoperative bleeding.Methods:A total of 328 patients with CT-guided percutaneous fly biopsy who were admitted to the Affiliated Hospital of Ningbo University School of Medicine from June 2019 to March 2021 were selected, and the general clinical data of the patients were retrospectively analyzed. The patients were divided into observation group and control group according to postoperative bleeding. Statistical analysis was performed on clinical data of patients with statistical significance, receiver operating characteristic (ROC) curve analysis on continuous variables with statistical significance, and Logistic multiple regression analysis on all variables with statistical significance. The risk factors of bleeding complications in CT-guided percutaneous lung biopsy were obtained, and a Nomogram model for predicting bleeding after percutaneous lung biopsy was constructed using the R language software 4.0 "rms" package.Results:The results of the study showed that the size of the mass , the depth of the mass, the number of punctures, the number of cases with inflammation around the lesion , and the number of cases with chronic lung lesions in the observation group were greater than those in the control group: (5.20 ± 1.20) cm vs. (4.30 ± 0.90) cm, (4.30 ± 0.60) cm vs. (2.90 ± 0.30) cm, (2.70 ± 0.60) times vs. (2.30 ± 0.50) times, 38(14, 70) cases vs. 17(24, 60) cases, 102(39, 40) cases vs. 41(59, 40) cases; while the number of normal preoperative prothrombin time (PT) in the observation group was less than that in the control group: 4(5, 80) cases vs. 151(58, 30) cases ( P<0.05). ROC curve analysis was performed on the continuous variables with statistical significance in the control table of patients′general clinical data. The results showed that the area under the curve for swelling size, swelling depth, number of punctures, and number of tissue blocks cut were 0.563, 0.714, 0.680, and 0.559, respectively; the optimal cut-off values were 53.00 cm, 5.56 cm, 2.00 times, and 1.00 blocks ( P<0.05). The univariate indicators were included in the Logistic multiple regression model, and the results showed that tumor depth, puncture times, inflammation around the lesion, and abnormal preoperative PT were the risk factors for complications of percutaneous lung biopsy under CT ( P<0.05). The internal validation results showed that the Nomogram model predicted the risk of bleeding complicated by percutaneous lung biopsy under CT, with a C index of 0.687 (95% CI 0.241 - 1.988). The calibration curve showed good agreement between the observed and predicted values. The Nomogram model predicted percutaneous lung biopsy under CT with a bleeding risk threshold of >0.16, and the Nomogram model provided a clinical net benefit; in addition, the Nomogram model had a higher clinical net benefit than independent indicators. Conclusions:In conclusion, patients with poor coagulation function, inflammation around tumor lesions, deeper lesions, and more puncture times are more prone to bleeding. The Nomogram model constructed in this study has a high clinical application value for predicting the bleeding complications of CT-guided percutaneous lung biopsy.

Long non-coding RNAs (lncRNAs) reportedly function as important modulators of gene regulation and malignant processes in the development of human cancers. The lncRNA JPX is a novel molecular switch for X chromosome inactivation and differentially expressed JPX has exhibited certain clinical correlations in several cancers. Notably, JPX participates in cancer growth, metastasis, and chemoresistance, by acting as a competing endogenous RNA for microRNA, interacting with proteins, and regulating some specific signaling pathways. Moreover, JPX may serve as a potential biomarker and therapeutic target for the diagnosis, prognosis, and treatment of cancer. The present article summarizes our current understanding of the structure, expression, and function of JPX in malignant cancer processes and discusses its molecular mechanisms and potential applications in cancer biology and medicine.
Humans ; RNA, Long Noncoding/genetics* ; Neoplasms/genetics* ; MicroRNAs/genetics* ; Gene Expression Regulation ; X Chromosome Inactivation

Oral bacteria directly affect the disease status of dental caries and periodontal diseases. The dynamic oral microbiota cooperates with the host to reflect the information and status of immunity and metabolism through two-way communication along the oral cavity and the systemic organs. The oral cavity is one of the most important interaction windows between the human body and the environment. The microenvironment at different sites in the oral cavity has different microbial compositions and is regulated by complex signaling, hosts, and external environmental factors. These processes may affect or reflect human health because certain health states seem to be related to the composition of oral bacteria, and the destruction of the microbial community is related to systemic diseases. In this review, we discussed emerging and exciting evidence of complex and important connections between the oral microbes and multiple human systemic diseases, and the possible contribution of the oral microorganisms to systemic diseases. This review aims to enhance the interest to oral microbes on the whole human body, and also improve clinician's understanding of the role of oral microbes in systemic diseases. Microbial research in dentistry potentially enhances our knowledge of the pathogenic mechanisms of oral diseases, and at the same time, continuous advances in this frontier field may lead to a tangible impact on human health.
Bacteria ; Dental Caries/microbiology* ; Humans ; Microbiota ; Mouth/microbiology* ; Mouth Diseases/microbiology* ; Periodontal Diseases/microbiology*

Objective:To develop a visualized nomogram with a predictive value to differentiate mass-forming chronic pancreatitis (MFCP) from pancreatic ductal adenocarcinoma (PDAC) patients with chronic pancreatitis (CP) history.Methods:The clinical and radiological data of 5 433 CP patients acoording to the Asia-Pacific Diagnostic Criteria between February 2011 and February 2021 in the First Affiliated Hospital of Naval Medical University were retrospectively analyzed, and 71 PDAC patients with CP history and 67 MFCP who underwent surgery or biopsy and pathologically confirmed were eventually enrolled. The training set included 44 patients with MFCP and 59 patients with PDAC who were diagnosed between February 2011 and April 2018. The validation set consisted of 23 patients with MFCP and 12 patients with PDAC who were diagnosed between May 2018 and February 2021. Univariate and multivariate logistic regression analyses were performed to develop a prediction model for PDAC and MFCP, and the model was visualized as a nomogram. ROC was used to evaluate the predictive efficacy of the nomogram, and the clinical usefulness was judged by decision curve analysis.Results:The univariate analysis showed that a significant association with pancreatic cancer were observed for the duct-to-parenchyma ratio ≥0.34, pancreatic duct cut-off, pancreatic portal hypertension, arterial CT attenuation, portal venous CT attenuation, delayed CT attenuation, and vascular invasion in both the training and validation cohorts, but the duct-penetrating sign in the training cohort only. The multivariable logistic regression analysis showed that statistically significant differences (all P value <0.05) existed in cystic degeneration, a duct-to-parenchyma ratio ≥0.34, the duct-penetrating sign, pancreatic portal hypertension and arterial CT attenuation between the two cohorts. The above parameters were selected for the logistic regression model. The predicted model=3.65-2.59×cystic degeneration+ 1.26×duct-to-parenchyma ratio≥0.34-1.40×duct-penetrating sign+ 1.36×pancreatic portal hypertension-0.05×arterial CT attenuation. Area under the curve, sensitivity, specificity and accuracy of the model-based nomogram were 0.87 (95 CI 0.80-0.94), 89.0%, 75.0% and 83.5% in the training cohort, and 0.94 (95 CI 0.82-0.99), 91.7%, 100% and 97.1% in the validation cohort, respectively. Decision curve analysis showed that when the nomogram differentiated MFCP from PDAC patients with CP history at a rate of 0.05-0.85, the application of the nomogram could benefit the patients. Conclusions:The nomogram based on CT radiological features accurately differentiated MFCP from PDAC patients with CP history and provide reference for guiding the treatment and judging the prognosis.

Objective:To develop and validate a visualized computed tomography nomogram for differentiating focal-type autoimmune pancreatitis (fAIP) from pancreatic ductal adenocarcinoma (PDAC).Methods:This retrospective review included 42 consecutive patients with fAIP diagnosed according to the International Consensus Diagnostic Criteria and 242 consecutive patients with PDAC confirmed by pathology between January 2011 and December 2018 in the First Affiliated Hospital of Naval Medical University. Among them, 209 consecutive patients (25 fAIP and 184 PDAC) were enrolled in the development cohort; Seventy-five consecutive patients (17 fAIP and 58 PDAC) were enrolled in the validation cohort. CT image characteristics, including lesion location, size, enhancement mode and degree of mass enhancement in portal vein phase, pancreatic parenchymal atrophy, main pancreatic duct dilation, common bile duct dilation, cyst, acute obstructive pancreatitis, and vascular invasion were compared. Univariate and multivariate analysis were used to screen the independent predictive factors for fAIP and PDAC, based on which the nomogram was constructed and visualized. The receiver operating characteristic curve (ROC) was drawn and area under the curve (AUC) was calculated to evaluate the differential efficacy of the nomogram. The clinical usefulness of the nomogram was evaluated by decision curve analysis.Results:There were statistically significant differences on common bile duct dilation and the mode and degree of enhancement in portal phase between fAIP group and PDAC group in training set and validation set ( P<0.05). Univariate regression analysis showed that common bile duct dilation and degree of mass enhancement in portal vein were closely correlated with fAIP and PDAC phase between the two groups in training set and validation set; mass enhancement mode in portal vein phase and main pancreatic duct dilation were closely correlated with fAIP and PDAC in training set. Multivariate logistic regression analysis showed that common biliary duct dilatation ( OR=0.26, 95% CI 0.06-1.10, P=0.07), main pancreatic duct dilation ( OR=9.46, 95% CI 1.60-56.04, P<0.01) and mass mild hyper-enhancing in portal vein phase ( OR=0.003, 95% CI 0.0003-0.0278, P<0.0001) were the three independent predictors for fAIP and PDAC. Thus, the equation for predicting the probability of PDAC was 4.51-1.33× no dilatation of the common bile duct+ 2.25× the main pancreatic duct dilated-5.84× mass mild hyper-enhancing during the portal phase. The individualized prediction nomogram using these predictors of the fAIP achieved an AUC of 0.97 (95% CI 0.95-0.99) in the development set and 0.97(95% CI0.94-1.00) in the validation set. The sensitivity, specificity and accuracy of the model were 87.5%, 100% and 89% in the training set; and 94.83%, 94.12% and 94.67% in the validation set, respectively. The decision curve analysis demonstrated that the nomogram was clinically useful when the nomogram differentiated fAIP and PDAC at a rate of >0.2. Conclusions:The nomogram based on common bile duct dilation, main pancreatic duct dilation and mass enhancement in portal vein phase can be used as a useful tool for predicting fAIP and PDAC and provide valuable evidence for clinical decision.

Objective:To investigate the relationship between the perineural invasion score based on multidetector computed tomography (MDCT) and extrapancreatic perineural invasion (EPNI) in pancreatic ductal adenocarcinoma (PDAC).Methods:The clinical, radiological, and pathological data of 374 patients pathologically diagnosed as pancreatic cancer who underwent radical resection in the First Affiliated Hospital of Naval Medical University from March 2018 to May 2020 were analyzed retrospectively. Patients were divided into EPNI negative group ( n=111) and EPNI positive group (n=263) based on the pathological presence of EPNI. The perineural invasion score was performed for each patient based on radiological images. Univariate and multivariate logistic regression models were used to analyze the association between the perineural invasion score based on MDCT and EPNI in PDAC. Results:There were significant statistical differences between EPNI negative group and positive group on both pathological characteristics (T stage, N stage, invasion of common bile duct, and positive surgical margin) and radiological characteristics (tumor size, vascular invasion, lymph node metastasis, perineural invasion score based on MDCT, pancreatic border, parenchymal atrophy, invasion of duodenum, invasion of spleen and splenic vein and invasion of common bile duct) (all P value <0.05). Univariate analysis revealed that the tumor size, vascular invasion, lymph node metastasis, perineural invasion score based on MDCT, pancreatic border, pancreatic atrophy, invasion of duodenum, invasion of spleen and splenic vein and invasion of common bile duct were independently associated with EPNI. Multivariate analyses revealed that the perineural invasion based on MDCT was an independent risk factor for EPNI in pancreatic cancer (score=1, OR=2.93, 95% CI 1.61-5.32, P<0.001; score=2, OR=5.92, 95% CI 2.68-13.10, P<0.001). Conclusions:The perineural invasion score based on MDCT was an independent risk factor for EPNI in pancreatic cancer and can be used as an evaluation indicator for preoperative prediction of EPNI in PDAC.